Image Classification
Transformers
Safetensors
English
clip
zero-shot-image-classification
multi-task-classification
fairface
vision
autoeval-has-no-ethical-license
Eval Results (legacy)
Instructions to use syntheticbot/clip-face-attribute-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syntheticbot/clip-face-attribute-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="syntheticbot/clip-face-attribute-classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("syntheticbot/clip-face-attribute-classifier") model = AutoModelForZeroShotImageClassification.from_pretrained("syntheticbot/clip-face-attribute-classifier") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -145,8 +145,7 @@ def predict(image_path):
|
|
| 145 |
return predictions
|
| 146 |
|
| 147 |
# --- 5. Run Prediction ---
|
| 148 |
-
|
| 149 |
-
# !wget -q https://huggingface.co/syntheticbot/clip-face-attribute-classifier/resolve/main/sample.jpg -O sample.jpg
|
| 150 |
predict('sample.jpg') # Replace with the path to your image
|
| 151 |
```
|
| 152 |
|
|
|
|
| 145 |
return predictions
|
| 146 |
|
| 147 |
# --- 5. Run Prediction ---
|
| 148 |
+
|
|
|
|
| 149 |
predict('sample.jpg') # Replace with the path to your image
|
| 150 |
```
|
| 151 |
|